At its best, freight technology grants shippers access to things they wouldn’t get ordinarily. Those things might be lower rates, more efficient use of resources, or visibility into the movement of goods.
But in times of tight supply, the most valuable commodity a technology can provide is the ability to access previously hidden capacity. A host of technology providers in the North American surface transportation space have released tools over the past year designed to do just that.
Sometimes those tools are aimed at freight brokers, allowing those intermediaries to give their shipper customers more capacity options. Sometimes the tools are designed to give shippers themselves the ability to unlock latent capacity in the system. The latter example lies at the blurry point where a software vendor actually functions like a digitally powered broker, or vice versa.
All of these tools are built around the concept of marrying the tracking of drivers and equipment with predictive algorithms that give insight as to where and when a driver and truck will be available. In essence, technology developed to track in-transit cargo has morphed into technology that predicts when capacity will be free.
Technology powers visibility
Three primary sources are powering that visibility: apps downloaded on a driver’s smartphone that enable GPS location; driver cell phone triangulation location; and electronic logging devices (ELDs) installed on all post-1999 engines that pinpoint the location of a cab.
Knowing where those drivers or cabs are allows software providers to match capacity with available loads provided by brokers or shippers. But layering in historical patterns, weather, demand signals, and other (often unstructured) data points allows those providers to provide predictive capacity, a term now entrenched in the trucking industry.
The next step, which technology providers say they are working toward, allows buyers of capacity to build sequential loads with the same trucker. That could transform spot buying into a more strategic process.
This drive to uncover capacity also is promoting creative solutions using advanced technologies that are just starting to get traction in the industry.
Some software providers, for example, are using an offshoot of artificial intelligence called natural language processing (NLP) to capture capacity in unstructured, and generally offline, communications between carriers and brokers. These tools scour for patterns in emails to determine if a carrier has capacity that matches an available load from a broker or carrier.
Using NLP and historical pattern analysis, brokers also can determine more quickly which carriers are likely to accept their loads.
Technology that uncovers latent trucking capacity largely attempts to empower smaller brokers and carriers to work with shippers they previously would have been unlikely to connect with. Conversely, it broadens the array of capacity options for shippers to include carriers and brokers they would have been unlikely to find.
The key principle behind this is that systems can work out problems at a speed and scale that humans cannot. It’s less efficient for brokers to pound the phones or scour online load boards than it is for a computer to work through those scenarios. But these systems still require density, and that’s where solutions providers still require boots on the ground to widen their network.
Along those lines, another innovation in recent years that contributes to unlocking hidden capacity is the concept of the free transportation management system (TMS). Some TMS providers give away a light version of their software to shippers and brokers simply to build up their networks of shippers and carriers. Those connections provide data to the software companies that allow them to build predictive capacity tools, among other things.
The advent of the so-called digital freight broker in recent years is probably the most obvious example of companies trying to directly match supply and demand in a more automated way. That model has been backed to the tune of hundreds of millions of dollars by venture capital firms that see the automation of load-matching as transformative.
But many existing brokers — especially the 10 largest in North America — say they have long invested in systems and algorithms that more efficiently match capacity and loads. In their view, digital brokers are nothing more than small brokers that spend a disproportionate amount on engineering and aren’t constrained by the profitability expectations that established companies are.
The question in 2019 is whether the drive to secure previously unknown pockets of capacity is as strong if the market evens out. Software providers say their solutions are valuable in every market condition. In looser markets, capacity-matching tools allow trucking companies to better understand where loads are available. And markets are never universal — there are always regions and lanes that will buck the national trend.